Biology subjects

Wang, Y. C.

Publications and source records attributed to Wang, Y. C..

12 recordsLinked to original sources

bioRxiv2025

Cerebrospinal fluid-driven ependymal motile cilia defects are implicated in multiple sclerosis pathophysiology

BackgroundMultiple sclerosis is a neurodegenerative autoimmune disorder of the central nervous system (CNS) in which autoreactive immune cells migrate through a damaged blood brain barrier, resulting in focal demyelinating lesions of both the white and grey matter. Of increasing interest is the repeated observation that beyond focal lesions, there are also diffuse, surface-in gradients of pathology in MS, wherein damage is most severe directly adjacent to cerebrospinal fluid (CSF)-contacting surfaces, such as the subpial and periventricular areas. This observation suggests that toxic factors within MS CSF may be contributing to the emergence and/or evolution of surface-in gradients. Directly separating the CSF from the periventricular parenchyma are ependymal cells - a glial epithelium that are equipped with tufts of motile cilia which are critical for circulating CSF solutes and regulating local fluid flow. While damage to ependymal cilia has the potential to drastically modify CSF homeostasis and thus contribute to the damage of CSF exposed regions, these motile cellular structures have yet to be investigated in the context of MS. MethodsWe first conducted single cell RNA sequencing of fresh human periventricular brain tissue containing ependymal cells from MS patients and non-MS disease controls. We subsequently collected CSF from MS patients and exposed cultured rodent ependymal cells to this CSF in order to evaluate impact on ependymal ciliary function. To complement our direct evaluation of cilia in the context of MS, we also confirmed whether cilia were altered in a classic animal model of MS, experimental autoimmune encephalomyelitis (EAE), and also designed a novel transgenic animal model to evaluate the cellular and behavioural effect(s) of adult ependymal ciliary disruption. ResultsSingle cell RNA sequencing analysis of human ependymal cells in MS demonstrated largescale dysregulation of ciliary genes and in situ stains of MS brain tissue confirmed a loss of ependymal cilia. Exposure of ependymal cells to MS CSF led to transcriptional modification of ciliary gene and protein expression and reduced ciliary beating frequency. Likewise, analysis of ependymal cells in EAE also demonstrated altered cilia gene and protein expression. Conditional knockout in adult mice, of the critical cilia-associated gene Ccdc39 in ependymal cells led to transient ventricular enlargement, increased periventricular microglial density, and alterations in nesting behaviour. ConclusionThese data suggest that motile cilia in ependymal cells are dysregulated in CNS autoimmunity. More importantly, however, they provide evidence to suggest that ependymal cilia disruption could play an active role in the development of periventricular pathology in MS and can lead to behavioural deficits that may underlie aspects non-motor MS symptomatology.

neuroscience↗

bioRxiv2025

Recombination alters the furin cleavage site in novel bat-borne HKU5-CoV-2 coronavirus

HKU5-CoV-2 is a new bat-infecting coronavirus phylogenetically related to MERS-CoV. It has recently been confirmed that HKU5-CoV-2 can enter human cells and organoids in vitro via the ACE2 receptor, raising concerns about its pandemic potential due to zoonotic spillover. Whether recombination has an influence on HKU5-CoV-2 is completely unclear to date. Here we report the first evidence of HKU5-CoV-2 viral recombination, in association with mutations at the receptor binding domain (RBD) and S1/S2 furin cleavage site (FCS) of the spike protein. Using linkage disequilibrium and haploblock analysis, we identified that 167 recombination hotspots and 27 haploblocks. SNP23016/23043/23064/23156/23193/23285 at the RBD and SNP23833/23847 at the FCS are recombinant hotspots. Our results suggest that recombination may lead to the substitution at RBD residue 498 (Thr498Val/Val498Thr, Thr498Ile/Ile498Thr), which Thr498 directly contacts the ACE2 receptor. Recombination also causes Ser723 deletion/insertion and Ser729Ala substitution at the FCS. These mutations could affect host tropism and change furin cleavage activity. Our results indicate that recombination has played a critical role in HKU5-CoV-2 evolution and infectivity.

microbiology↗

bioRxiv2023

Inhibition of Type I PRMTs Reforms Muscle Stem Cell Identity Enhancing their Therapeutic Capacity

In skeletal muscle, muscle stem cells (MuSC) are the main cells responsible for regeneration upon injury. In diseased skeletal muscle, it would be therapeutically advantageous to replace defective MuSCs, or rejuvenate them with drugs to enhance their self-renewal and ensure long-term regenerative potential. One limitation of the replacement approach has been the inability to efficiently expand MuSCs ex vivo, while maintaining their stemness and engraftment abilities. Herein, we show that inhibition of type I protein arginine methyltransferases (PRMTs) with MS023 increases the proliferative capacity of ex vivo cultured MuSCs. Single cell RNA sequencing (scRNAseq) of ex vivo cultured MuSCs revealed the emergence of subpopulations in MS023-treated cells which are defined by elevated Pax7 expression and markers of MuSC quiescence, both features of enhanced self-renewal. Furthermore, the scRNAseq identified MS023-specific subpopulations to be metabolically altered with upregulated glycolysis and oxidative phosphorylation (OxPhos). Transplantation of MuSCs treated with MS023 had a better ability to repopulate the MuSC niche and contributed efficiently to muscle regeneration following injury. Interestingly, the preclinical mouse model of Duchenne muscular dystrophy had increased grip strength with MS023 treatment. Our findings show that inhibition of type I PRMTs increased the proliferation capabilities of MuSCs with altered cellular metabolism, while maintaining their stem-like properties such as self-renewal and engraftment potential.

molecular biology↗

bioRxiv2022

Supercomputers and Reverse Engineering of Motoneuron Firing Patterns

In this study, we develop new reverse engineering (RE) techniques to identify the organization of the synaptic inputs generating firing patterns of populations of neurons. We tested these techniques in silico to allow rigorous evaluation of their effectiveness, using remarkably extensive parameter searches enabled by massively-parallel computation on supercomputers. We chose spinal motoneurons as our target neural system, since motoneurons process all motor commands and have well established input-output properties. One set of simulated motoneurons was driven by 300,000+ simulated combinations of excitatory, inhibitory, and neuromodulatory inputs. Our goal was to determine if these firing patterns had sufficient information to allow RE identification of the input combinations. Like other neural systems, the motoneuron input-output system is likely non-unique. This non-uniqueness could potentially limit this RE approach, as many input combinations can produce similar outputs. However, our simulations revealed that firing patterns contained sufficient information to sharply restrict the solution space. Thus, our RE approach successfully generated estimates of the actual simulated patterns of excitation, inhibition, and neuromodulation, with variances accounted for ranging from 75% to 90%. It was striking that nonlinearities induced in firing patterns by the neuromodulation inputs did not impede RE, but instead generated distinctive features in firing patterns that aided RE. These simulations demonstrate the potential of this form of RE analysis. It is likely that the ever-increasing capacity of supercomputers will allow increasingly accurate RE of neuron inputs from their firing patterns from many neural systems.

neuroscience↗

bioRxiv2022

Improved Nanopore full-length cDNA sequencing by PCR-suppression

Full-length transcript sequencing remains a main goal of RNA sequencing. However, even the application of long-read sequencing technologies such as Oxford Nanopore Technologies still fail to yield full-length transcript sequencing for a significant portion of sequenced reads. Since these technologies can sequence reads that are far longer than the longest known processed transcripts, the lack of efficiency to obtain full-length transcripts from good quality RNAs stems from library preparation inefficiency rather than the presence of degraded RNA molecules. It has previously been shown that addition of inverted terminal repeats in cDNA during reverse transcription followed by single-primer PCR creates a PCR suppression effect that prevents amplification of short molecules thus enriching the library for longer transcripts. We adapted this method for Nanopore cDNA library preparation and show that not only is PCR efficiency increased but gene body coverage is dramatically improved. The results show that implementation of this simple strategy will result in better quality full-length RNA sequencing data and make full-length transcript sequencing possible for most of sequenced reads. Contribution to the fieldLong-read RNA sequencing aims to sequence expressed transcripts in their entirety. However, this has remained a challenge, mainly due to inherent inefficiencies in cDNA library preparation. Herein, we provide a new Nanopore cDNA library preparation protocol, termed Panhandle, that improves the efficiency of cDNA PCR with yields 2 - 8 times the yields obtained with ordinary PCR. This is key, as this should in turn reflect in the possibility of lowering the number of PCR cycles needed to obtain ample sequencing material, which in turn could reduce PCR biases, PCR artifacts, turnaround time, reagents, and could increase general quality of the library. Further, transcripts generated using the Panhandle method show better gene body coverage and more accurate transcription start site mapping than regular methods. This represents an important step towards full-length cDNA sequencing by Nanopore.

genomics↗

bioRxiv2021

Algorithmic Parameter Estimation and Uncertainty Quantification for Hodgkin-Huxley Neuron Models

Experimental data-based parameter search for Hodgkin-Huxley-style (HH) neuron models is a major challenge for neuroscientists and neuroengineers. Current search strategies are often computationally expensive, are slow to converge, have difficulty handling nonlinearities or multimodalities in the objective function, or require good initial parameter guesses. Most important, many existing approaches lack quantification of uncertainties in parameter estimates even though such uncertainties are of immense biological significance. We propose a novel method for parameter inference and uncertainty quantification in a Bayesian framework using the Markov chain Monte Carlo (MCMC) approach. This approach incorporates prior knowledge about model parameters (as probability distributions) and aims to map the prior to a posterior distribution of parameters informed by both the model and the data. Furthermore, using the adaptive parallel tempering strategy for MCMC, we tackle the highly nonlinear, noisy, and multimodal loss function, which depends on the HH neuron model. We tested the robustness of our approach using the voltage trace data generated from a 9-parameter HH model using five levels of injected currents (0.0, 0.1, 0.2, 0.3, and 0.4 nA). Each test consisted of running the ground truth with its respective currents to estimate the model parameters. To simulate the condition for fitting a frequency-current (F-I) curve, we also introduced an aggregate objective that runs MCMC against all five levels simultaneously. We found that MCMC was able to produce many solutions with acceptable loss values (e.g., for 0.0 nA, 889 solutions were within 0.5% of the best solution and 1,595 solutions within 1% of the best solution). Thus, an adaptive parallel tempering MCMC search provides a "landscape" of the possible parameter sets with acceptable loss values in a tractable manner. Our approach is able to obtain an intelligently sampled global view of the solution distributions within a search range in a single computation. Additionally, the advantage of uncertainty quantification allows for exploration of further solution spaces, which can serve to better inform future experiments.

neuroscience↗

bioRxiv2020

A thousand metagenome-assembled genomes of Akkermansia reveal new phylogroups and geographical and functional variations in human gut

The present study revealed the genomic architecture of Akkermansia in human gut by analyzing 1,119 near-complete metagenome-assembled genomes, 84 public available genomes, and 1 newly sequenced A. glycaniphila strain. We found that 1) the genomes of Akkermansia formed 4 species (including 2 candidate species) with distinct interspecies similarity and differed genomic characteristics, and 2) the population of A. muciniphila was structured by 3 previously identified phylogroups (Amuc I, II, and III) referring to 1,132 genomes and 1 new phylogroup (defined as Amuc IV) that contained 62 genomes. Amuc III was presented in Chinese population and Amuc IV was mainly distributed in western populations. A large number of gene of functions, pathways, and carbohydrate active enzymes that specifically associated to phylogroups. Our findings based on over a thousand genomes strengthened the previous knowledge and provided new insights into the population structure and ecology of Akkermansia in human gut.

genomics↗

bioRxiv2020

Oviduct epithelial cells constitute two developmentally distinct lineages that are spatially separated along the distal-proximal axis

Owing to technical advances in single cell biology, the appreciation of cellular heterogeneity has increased, which has aided our understanding of organ function, homeostasis and disease progression. The oviduct (also known as the fallopian tube in humans) is the distal-most portion of the female reproductive tract. It is essential for reproduction and the proposed origin of high grade serous ovarian carcinoma (HGSOC). In mammals, the oviduct is morphologically segmented along the ovary-uterus axis into four evolutionally conserved regions. It is unknown however if there is a diversification of epithelial cell characteristics between these regions. In this study, we identified transcriptionally distinct populations of secretory and multiciliated cells restricted to the distal and proximal regions of the oviduct. We demonstrated that these distal and proximal populations are distinct lineages specified early in Mullerian duct development and are maintained separately. These results aid our understanding of epithelial development, homeostasis and initiation of disease from the oviduct.

developmental biology↗

bioRxiv2020

Predictive Neural Computations Support Spoken Word Recognition: Evidence from MEG and Competitor Priming

Human listeners achieve quick and effortless speech comprehension through computations of conditional probability using Bayes rule. However, the neural implementation of Bayesian perceptual inference remains unclear. Competitive-selection accounts (e.g. TRACE) propose that word recognition is achieved through direct inhibitory connections between units representing candidate words that share segments (e.g. hygiene and hijack share /haid{ezh}/). Manipulations that increase lexical uncertainty should increase neural responses associated with word recognition when words cannot be uniquely identified. In contrast, predictive-selection accounts (e.g. Predictive-Coding) proposes that spoken word recognition involves comparing heard and predicted speech sounds and using prediction error to update lexical representations. Increased lexical uncertainty in words like hygiene and hijack will increase prediction error and hence neural activity only at later time points when different segments are predicted. We collected MEG data from male and female listeners to test these two Bayesian mechanisms and used a competitor priming manipulation to change the prior probability of specific words. Lexical decision responses showed delayed recognition of target words (hygiene) following presentation of a neighbouring prime word (hijack) several minutes earlier. However, this effect was not observed with pseudoword primes (higent) or targets (hijure). Crucially, MEG responses in the STG showed greater neural responses for word-primed words after the point at which they were uniquely identified (after /haid{ezh}/ in hygiene) but not before while similar changes were again absent for pseudowords. These findings are consistent with accounts of spoken word recognition in which neural computations of prediction error play a central role. Significance StatementEffective speech perception is critical to daily life and involves computations that combine speech signals with prior knowledge of spoken words; that is, Bayesian perceptual inference. This study specifies the neural mechanisms that support spoken word recognition by testing two distinct implementations of Bayes perceptual inference. Most established theories propose direct competition between lexical units such that inhibition of irrelevant candidates leads to selection of critical words. Our results instead support predictive-selection theories (e.g. Predictive-Coding): by comparing heard and predicted speech sounds, neural computations of prediction error can help listeners continuously update lexical probabilities, allowing for more rapid word identification.

neuroscience↗

bioRxiv2019

The Genomic Stability at the Coding Regions of the Multidrug Transporter Gene ABCB1: Insights into the Development of Alternative Drug Resistance Mechanisms in Human Leukemia Cells

Despite considerable efforts in reversing clinical multidrug resistance (MDR), targeting the predominant multidrug transporter ABCB1/P-glycoprotein (P-gp) based on small molecule inhibitors has been hindered. This may be due to the emergence of alternative drug resistance mechanisms. However, the non-specific P-gp inhibitor cyclosporine (CsA) showed significant clinical benefits in patients with acute myeloid leukemia (AML), which likely represents the only proof-of-principle clinical trial using several generations of MDR inhibitors. Nevertheless, the mechanisms that underlie this successful MDR modulation by CsA are not elucidated because of the absence of CsA-relevant cellular models. In this study, we report the development of two erythroleukemia variants, RVC and RDC, which were derived by step-wise co-selection of K562/R7 drug-resistant leukemia cells with the etoposide-CsA and doxorubicin-CsA drug combinations, respectively. Interestingly, both RVC and RDC, which retained P-gp expression, showed altered MDR phenotypes that were resistant to cyclosporine modulation. The ABCB1 coding regions were genetically stable even under long-term stringent drug selection. Genomically, ABCB1 is likely the most stable ABC transporter gene when comparing with several ABC superfamily members (such as ABCA1, ABCC1, CFTR, and ABCG2). Our findings suggested that non-P-gp mechanisms were likely responsible for the resistance to CsA modulation in both RVC and RDC cells. Moreover, we found that CsA played a role in undermining the selection of highly drug-resistant cells via induction of low level and unstable drug resistance, thus shedding some light on the benefits of CsA in treating certain types of AML patients.

cancer biology↗

bioRxiv2019

Single-cell analysis of childhood leukemia reveals a link between developmental states and ribosomal protein expression as a source of intra-individual heterogeneity

Childhood acute lymphoblastic leukemia (cALL) is the most common pediatric cancer. It is characterized by bone marrow lymphoid precursors that acquire genetic alterations, resulting in disrupted maturation and uncontrollable proliferation. More than a dozen molecular subtypes of variable severity can be used to classify cALL cases. Modern therapy protocols currently cure 85-90% of cases, but other patients are refractory or will relapse and eventually succumb to their disease. To better understand these difficult cases, we investigated the nature and extent of intra-individual transcriptional heterogeneity of cALL at the cellular level by sequencing the transcriptomes of 39,375 individual cells in eight patients (six pre-B and two pre-T) and three healthy pediatric controls. We observed intra-individual transcriptional clusters in five out of the eight patients. Using pseudotime maturation trajectories of healthy B and T cells, we obtained the predicted developmental state of each leukemia cell and observed distribution shifts within patients. We showed that the predicted developmental states of these cancer cells are inversely correlated with ribosomal protein expression levels, which could be a common contributor to intra-individual heterogeneity in cALL patients.

cancer biology↗

bioRxiv2018

Transcriptome landscape of the developing olive fruit fly embryo delineated by Oxford Nanopore long-read RNA-Seq

The olive fruit fly or olive fly (Bactrocera oleae) is the most important pest of cultivated olive trees. Like all insects the olive fly undergoes complete metamorphosis. However, the transcription dynamics that occur during early embryonic development have not been explored, while detailed transcriptomic analysis in the absence of a fully annotated genome is challenging. We collected olive fly embryos at hourly intervals for the first 6 hours of development and performed full-length cDNA-Seq using a purpose designed SMARTer cDNA synthesis protocol followed by sequencing on the MinION (Oxford Nanopore Technologies). We generated 31 million total reads across the timepoints (median yield 4.2 million per timepoint). The reads showed 98 % alignment rate to the olive fly genome and 91 % alignment rate to the NBCI predicted B. oleae gene models. Over 50 % of the expressed genes had at least one read covering its entire length validating our full-length RNA-Seq procedure. Expression of 68 % of the predicted B. oleae genes was detected in the first six hours of development. We generated a de novo transcriptome assembly of the olive fly and identified 3553 novel genes and a total of 79,810 transcripts; a fourfold increase in transcriptome diversity compared to the NCBI predicted transcriptome. On a global scale, the first six hours of embryo development were characterized by dramatic transcriptome changes with the total number of transcripts per embryo dropping to half from the first hour to the second hour of embryo development. Clustering of genes based on temporal co-expression followed by gene-set enrichment analysiss of genes expressed in the first six hours of embryo development showed that genes involved in transcription and translation, macro-molecule biosynthesis, and neurodevelopment were highly enriched. These data provide the first insight into the transcriptome landscape of the developing olive fly embryo. The data also reveal transcript signatures of sex development. Overall, full-length sequencing of the cDNA molecules permitted a detailed characterization of the isoform complexity and the transcriptional dynamics of the first embryonic stages of the B. oleae.

developmental biology↗